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labyrinth-analytics

LoreConvo

Official

Export Sessions

export_sessions

Export sessions to JSON or JSONL for backup or migration, with optional filtering by project, tags, and recency. Choose file output or inline data.

Instructions

Export sessions to JSON or JSONL for backup or migration.

Exports all matching sessions with full detail (including skills, tags, artifacts). Use output_path to write to a file; omit it to receive the data inline. Use import_sessions to load the exported file.

Args: output_path: File path to write export (e.g. '/tmp/loreconvo_export.json'). If omitted, data is returned inline. project: Export only sessions from this project. tags: Export only sessions that have any of these tags. days_back: Limit to sessions from the last N days. Omit for all time. limit: Max sessions to export (default 1000). format: 'json' (array wrapped in metadata) or 'jsonl' (one session per line).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNo
limitNo
formatNojson
projectNo
days_backNo
output_pathNo
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses that the export includes full detail (skills, tags, artifacts) and explains output_path behavior. However, it does not mention whether the operation is read-only, any authorization needs, or potential side effects. Basic behavioral context is present but lacks depth.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is concise and well-structured: a purpose sentence followed by an Arg list. Every sentence adds value, and key information is front-loaded. No redundant or verbose phrasing.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 6 parameters and no output schema or annotations, the description covers the core functionality, parameter semantics, and inline vs file behavior. It does not specify the structure of inline return data or error handling (e.g., file overwrite), but it is largely complete for the tool's purpose.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the description includes an Args section that explains each parameter (output_path, project, tags, days_back, limit, format) with context like default values and usage patterns. This adds significant meaning beyond the bare schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states the tool exports sessions to JSON/JSONL for backup/migration. The verb 'export' and resource 'sessions' are specific, and the purpose is well-understood. However, it does not explicitly differentiate from sibling tools like get_session or search_sessions, which limits a top score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides clear guidance on using import_sessions to load exported data, and explains the output_path behavior (file vs inline). It does not specify when not to use this tool versus alternatives, but the mention of an explicit alternative is helpful.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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